Credit misuse costs financial institutions billions of dollars each year. One exemplary type of credit misuse occurs when an individual consumer draws down a line of credit with intent to defraud the financial institution by not repaying the “borrowed” money. For example, when perpetrating this type of credit misuse, to ostensibly appear as a creditworthy consumer, the individual consumer builds a good credit score by exhibiting good credit behavior for an extended period of time. Relying on the good credit score, the individual consumer obtains lines of credit, e.g., credit cards, personal loans, and business loans, and then draws down the approved credit with no intention to ever repay the money. The individual consumer may not necessarily draw down the credit immediately after the credit is approved, but, when the individual does drawn down the credit, to avoid detection, the individual draws down the credit in a short period, e.g., less than four months. Oftentimes, individual consumers perpetrating this type of credit misuse draw down credit by taking large cash advances.
Because individual consumers who perpetrate this type of credit misuse typically have good credit histories and credit scores at the time they apply for credit and because these individuals utilize most or all approved credit within a short period, historical information provided in traditional credit reports is too dated to be useful for detecting the fraudulent nature of these individuals' financial transactions before the individuals draw down the credit. Traditional credit reports are based on information that is at least a month old. For example, to generate traditional credit reports, consumer reporting agencies (“CRAs”) collect—on a monthly basis—personal and financial information about individual consumers and update each individual's credit report to include information from the previous month.
More specifically, CRAs collect personal and financial information about individual consumers from a variety of sources called data furnishers. These data furnishers are typically institutions that have had financial relationships with individual consumers. For example, data furnishers may be creditors, lenders, utility companies, debt-collection agencies, government agencies, and courts. Data furnishers report data regarding individual consumers to CRAs on a monthly basis, and, based on the received data, CRAs generate a credit report or update an existing credit report for each individual consumer.
A typical credit report contains detailed information about an individual consumer's credit history, including credit accounts and loans, bankruptcies, past due payments, and recent inquiries. A typical credit report also contains credit-utilization information, which indicates the percentage of approved credit an individual has actually used. Individuals utilizing a high percentage of their approved credit are generally more risky than those utilizing a low percentage. Also, a typical credit report contains a credit score, which, as mentioned above, reflects an individual consumer's creditworthiness. CRAs typically calculate creditworthiness scores on a monthly basis using the information provided by data furnishers.
Because credit reports, including creditworthiness scores, are updated on a monthly basis, individuals who draw down credit in a single month may avoid detection. For example, during the month an individual perpetrating the above-described type of credit misuse draws down most or all available credit, that individual's credit report may indicate low credit utilization and timely payment histories. Not until a month after the individual has exhausted lines of credit will that individual's credit report indicate high credit utilization, and not until several months after the individual has stopped making payments will that individual's credit report indicate missed payments. Accordingly, there is a need for systems, devices, methods, computer program products and other tools that identify transactions predictive of credit fraud and that enable financial institutions to utilize proactive measures to thwart fraudulent schemes and reduce losses resulting from credit fraud.